@article {10.3844/ajassp.2017.726.736,
article_type = {journal},
title = {Identification of Characteristics of Land Cover in Mangkauk Catchment Area Using Support Vector Machine (SVM) And Artificial Neural Network (ANN)},
author = {Ridwan, Ichsan and Bisri, Mohammad and Yusran, Fadly Hairannoor and Hakim, Luchman and Kadir, Syarifuddin},
volume = {14},
year = {2017},
month = {Jul},
pages = {726-736},
doi = {10.3844/ajassp.2017.726.736},
url = {https://thescipub.com/abstract/ajassp.2017.726.736},
abstract = {Land cover is anything that includes any types of appearance on the surface of the earth on a particular land. Information related to land cover can be used as at the parameter to determine the amount of runoff in a catchment area. This study was conducted in the Catchment Area (CA) of Mangkauk using Landsat 8 OLI/TIRS 2014 scene path/row 117/62 with the methods of Support Vector Machine (SVM) and Artificial Neural Network (ANN). The classification of land cover in Mangkauk catchment area included forests, plantations, shrubs, reeds/grasses, rice fields, open lands, settlements and water body. Based on the accuracy test of land cover classification using SVM, the value of the overall accuracy was 97.22% with Kappa Coefficient 0.96, while using ANN 86.33% with Kappa Coefficient 0.79.},
journal = {American Journal of Applied Sciences},
publisher = {Science Publications}
}